Apple:

At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy principles, and one of those principles is to prioritize using on-device processing. By performing computations locally on a user’s device, we help minimize the amount of data that is shared with Apple or other entities. Of course, a user may request on-device experiences powered by machine learning (ML) that can be enriched by looking up global knowledge hosted on servers. To uphold our commitment to privacy while delivering these experiences, we have implemented a combination of technologies to help ensure these server lookups are private, efficient, and scalable.

One of the key technologies we use to do this is homomorphic encryption (HE), a form of cryptography that enables computation on encrypted data (see Figure 1). HE is designed so that a client device encrypts a query before sending it to a server, and the server operates on the encrypted query and generates an encrypted response, which the client then decrypts. The server does not decrypt the original request or even have access to the decryption key, so HE is designed to keep the client query private throughout the process.